Using semi-structured data for assessing research paper similarity

Information Sciences

Volumn 221, Issue , 2013, Pages 245-261

  Martín, Germán Hurtado ^a,b   Schockaert, Steven ^c   Cornelis, Chris ^b,d   Naessens, Helga ^a  

^a UNIVERSITY COLLEGE GHENT   (Belgium)

^b GHENT UNIVERSITY   (Belgium)

^c CARDIFF UNIVERSITY   (United Kingdom)

^d UNIVERSITY OF GRANADA   (Spain)

Author keywords

Document similarity; Language modeling; Latent Dirichlet Allocation; Semi structured document

Indexed keywords

ABSTRACTING; COMPUTATIONAL LINGUISTICS; DEEP NEURAL NETWORKS; SEMANTICS; STATISTICS; VECTOR SPACES;

APPLICATION CONTEXTS; DOCUMENT SIMILARITY; EXPERIMENTAL ANALYSIS; EXPLICIT SEMANTIC ANALYSIS; LANGUAGE MODEL; LATENT DIRICHLET ALLOCATION; SEMI STRUCTURED DATA; SEMI-STRUCTURED DOCUMENTS;

MODELING LANGUAGES;

EID: 84884205127     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2012.09.044     Document Type: Article

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